Traumatic brain injury in homeless and marginally housed individuals: a systematic review and meta-analysis
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Introduction
More than 6
million people experience homelessness annually
in the USA and the EU.1
Homeless individuals experience markedly
poorer mental and physical health than the
general population, including a high prevalence
of psychotic disorders, major depression, and
drug and alcohol dependence,2
and a high prevalence of infectious
diseases, including HIV, hepatitis C, and
tuberculosis.3
Homeless and similarly marginalised
individuals also have substantially higher
all-cause mortality than the general
population.4
Traumatic brain injury (TBI) is a
pervasive and under-recognised public health
problem.5
TBI is associated with a number of
deleterious outcomes, with meta-analytic
evidence providing a link for the subsequent
development of neurological and psychiatric
disorders.6
TBI is often preventable, and thus might
represent a modifiable risk factor for serious
psychiatric illness and neurodegenerative
disease.
1.
Fazel, S ∙
Geddes, JR ∙
Kushel, M
The
health of
homeless
people in
high-income
countries:
descriptive
epidemiology,
health
consequences,
and clinical
and policy
recommendations
Lancet.
2014;
384:1529-1540
2.
Fazel, S ∙
Khosla, V ∙
Doll, H ∙ et al.
The
prevalence
of mental
disorders
among the
homeless in
western
countries:
systematic
review and
meta-regression
analysis
PLoS
Med.
2008;
5:e225
3.
Beijer, U ∙
Wolf, A ∙ Fazel,
S
Prevalence
of
tuberculosis,
hepatitis C
virus, and
HIV in
homeless
people: a
systematic
review and
meta-analysis
Lancet
Infect
Dis.
2012;
12:859-870
4.
Aldridge, RW ∙
Story, A ∙
Hwang, SW ∙ et
al.
Morbidity
and
mortality in
homeless
individuals,
prisoners,
sex workers,
and
individuals
with
substance
use
disorders in
high-income
countries: a
systematic
review and
meta-analysis
Lancet.
2018;
391:241-250
5.
Maas, AIR ∙
Menon, DK ∙
Adelson, PD ∙ et
al.
Traumatic
brain
injury:
integrated
approaches
to improve
prevention,
clinical
care, and
research
Lancet
Neurol.
2017;
16:987-1048
6.
Perry, DC ∙
Sturm, VE ∙
Peterson, MJ ∙
et al.
Association
of traumatic
brain injury
with
subsequent
neurological
and
psychiatric
disease: a
meta-analysis
J
Neurosurg.
2016;
124:511-526
Obtaining
reliable estimates of TBI incidence and lifetime
prevalence in the homeless and marginally housed
population, as well as in the general
population, has been challenging. Reported
incidence of TBI varies widely across
counties,5
and the methods of sampling participants
and defining TBI cases differ between reports.
Considerably higher rates of TBI have been
reported in population-based studies that
capture injuries for which medical attention is
not sought,7,8
as compared with studies that gather
data from medical records or emergency
departments.9,10
Additional sources of bias also exist,
including in the common definitions of TBI,5
and sampling or referral biases.
Similarly, the method for ascertaining history
of TBI has not been unanimously agreed upon and
estimates of the lifetime prevalence of TBI vary
considerably. Meta-analytic work has found that
12% of the general population reported at least
one TBI over the lifespan.11
A 2018 state-wide study in Ohio, USA,
which used a modified version of the
comprehensive Ohio State University TBI
ascertainment method (a short, structured
interview based on the Centers for Disease
Control definition of TBI and endorsed by the
National Institute of Neurological Disorders and
Stroke),12
found an estimated lifetime prevalence
of TBI of 21·7% in the general population, and a
lifetime prevalence of moderate or severe TBI of
2·6%.8
Although several tools designed to
ascertain TBI history are available (eg, the
Ohio State University TBI ascertainment
method13
and the Brain Injury Screening
Questionnaire),14
these methods have been inconsistently
used in studies of homeless and marginally
housed individuals.
5.
Maas, AIR ∙
Menon, DK ∙
Adelson, PD ∙ et
al.
Traumatic
brain
injury:
integrated
approaches
to improve
prevention,
clinical
care, and
research
Lancet
Neurol.
2017;
16:987-1048
7.
Feigin, VL ∙
Theadom, A ∙
Barker-Collo, S
∙ et al.
Incidence
of traumatic
brain injury
in New
Zealand: a
population-based
study
Lancet
Neurol.
2013;
12:53-64
8.
Corrigan, JD ∙
Yang, J ∙
Singichetti, B ∙
et al.
Lifetime
prevalence
of traumatic
brain injury
with loss of
consciousness
Inj
Prev.
2018;
24:396-404
9.
Majdan, M ∙
Plancikova, D ∙
Brazinova, A ∙
et al.
Epidemiology
of traumatic
brain
injuries in
Europe: a
cross-sectional
analysis
Lancet
Public
Health.
2016;
1:e76-e83
10.
Colantonio, A ∙
Saverino, C ∙
Zagorski, B ∙ et
al.
Hospitalizations
and
emergency
department
visits for
TBI in
Ontario
Can J
Neurol
Sci.
2010;
37:783-790
5.
Maas, AIR ∙
Menon, DK ∙
Adelson, PD ∙ et
al.
Traumatic
brain
injury:
integrated
approaches
to improve
prevention,
clinical
care, and
research
Lancet
Neurol.
2017;
16:987-1048
11.
Frost, RB ∙
Farrer, TJ ∙
Primosch, M ∙ et
al.
Prevalence
of traumatic
brain injury
in the
general
adult
population:
a
meta-analysis
Neuroepidemiology.
2013;
40:154-159
12.
Maas, AI ∙
Harrison-Felix,
CL ∙ Menon, D ∙
et al.
Standardizing
data
collection
in traumatic
brain
injury
J
Neurotrauma.
2011;
28:177-187
8.
Corrigan, JD ∙
Yang, J ∙
Singichetti, B ∙
et al.
Lifetime
prevalence
of traumatic
brain injury
with loss of
consciousness
Inj
Prev.
2018;
24:396-404
13.
Corrigan, JD ∙
Bogner, J
Initial
reliability
and validity
of the Ohio
State
University
TBI
Identification
Method
J Head
Trauma
Rehabil.
2007;
22:318-329
14.
Dams-O'Connor,
K ∙ Cantor, JB ∙
Brown, M ∙ et
al.
Screening
for
traumatic
brain
injury:
findings and
public
health
implications
J Head
Trauma
Rehabil.
2014;
29:479-489
Research in context
Evidence before this study
Previous studies and a previous
systematic review have suggested
that the lifetime prevalence and
incidence of TBI might be
considerably higher in homeless and
marginally housed individuals than
in the general population. Moreover,
many of these studies report that
TBI is associated with poorer health
or functioning in these individuals.
Marked methodological variation
exists among previous studies,
including in the tools used to
ascertain a history of TBI, in the
study-specific definitions of TBI,
and in the outcome measures
assessed. This variation limits our
understanding of the prevalence,
incidence, and impact of TBI in this
population. To date, no
meta-analyses have been done to
evaluate the prevalence of TBI in
homeless and marginally housed
individuals, nor have any
quantitative analyses of
heterogeneity among previous studies
been done. In preparation for this
review, we did systematic searches
in MEDLINE, Embase, PsycINFO,
CINAHL, and Web of Science for
studies that evaluated TBI in
homeless or marginally housed study
samples. Specific database search
terms are outlined in the appendix.
Studies were eligible for inclusion
if they evaluated the prevalence or
incidence of TBI, or the association
between TBI and health-related or
functioning-related outcome
measures, and they were original
peer-reviewed studies in the English
language. No date restrictions were
applied.
Added value of this study
To
our knowledge, this is the first
meta-analysis to evaluate the
prevalence of TBI in homeless and
marginally housed individuals and
the first quantitative assessment of
heterogeneity among studies that
assess TBI in this population. We
show that homeless and marginally
housed individuals experience a high
lifetime prevalence of TBI, and
notably, a lifetime prevalence of
moderate or severe TBI that is
approximately ten-times higher than
estimates in the general population.
We found high heterogeneity among
studies and our meta-regression
analyses identified several factors
that moderated individual study
findings. Our review also found that
TBI is associated with poorer
self-reported health, higher
suicidality and suicide risk,
increased health service use, and
increased criminal justice system
involvement.
Implications of all the available
evidence
TBI
is a pervasive and largely
under-recognised factor associated
with the poorer health and
functioning experienced by homeless
and marginally housed populations.
Our findings suggest that
health-care providers who work with
these individuals should be aware of
the high prevalence of TBI and
associated effects on health and
functioning. Additionally, given the
high prevalence of moderate or
severe TBI, and the considerable
number of individuals with evidence
of traumatically-induced lesions
visible with MRI, the threshold for
referral to neuroimaging specialists
after head injury should be reduced
in this population. Further research
is urgently needed to address
limitations to our understanding of
the burden of TBI in at-risk and
multimorbid populations. However, in
light of the significant moderating
factors that we identified, future
studies should carefully consider
and clearly describe all aspects of
study design to maximise validity
and clinical relevance.
A previous
systematic review that summarised eight studies
published between 1996 and 2012 found that
estimates of the lifetime prevalence of TBI in
homeless populations ranged from 8% to 53%.15
The most commonly identified
methodological limitations included poor
external validity and reporting of power
calculations. The authors also noted that TBI
was not a primary aim for the majority of
studies, and that important factors, such as
symptom burden and injury severity, were rarely
evaluated. Only three studies identified by the
previous review evaluated severity of TBI,
precluding systematic evaluation of the effects
of more clinically significant brain injuries.
The authors concluded that there were
considerable methodological limitations and
heterogeneity across available studies, and that
a strong need existed for larger studies with
validated and comprehensive measures, and
longitudinal designs.15
In subsequent years, as the potential
importance of TBI in these vulnerable
individuals has become increasingly recognised,
a number of larger and more comprehensive
studies have been published. Several of these
more recent studies have specifically examined
the impact of moderate or severe TBI in this
population, and several have addressed other
limitations highlighted by the previous review.
However, to the best of our knowledge, no
meta-analytic estimates of TBI prevalence in
homeless or marginally housed individuals have
been reported, nor has there been a
comprehensive review of the association between
TBI and health or functioning (eg,
neurocognitive function or day-to-day
functioning, such as employment) in these
individuals.
15.
Topolovec-Vranic,
J ∙ Ennis, N ∙
Colantonio, A ∙
et al.
Traumatic
brain injury
among people
who are
homeless: a
systematic
review
BMC Public
Health.
2012;
12,
1059
15.
Topolovec-Vranic,
J ∙ Ennis, N ∙
Colantonio, A ∙
et al.
Traumatic
brain injury
among people
who are
homeless: a
systematic
review
BMC Public
Health.
2012;
12,
1059
Evaluating the
prevalence and burden of TBI in individuals who
are homeless or marginally housed is critical to
understanding the unique challenges and
health-care needs of this population.
Furthermore, identifying factors that contribute
to heterogeneity across studies is integral to
establishing standardised approaches for future
research and in finding targets for the
prevention of TBI and treatment of its sequelae
in this population. In this study, we aimed to
estimate the lifetime prevalence of TBI in
homeless and marginally housed individuals, to
quantitatively evaluate factors that moderate
estimates of prevalence, and to systematically
review the association between TBI and health
and functioning-related outcome measures in this
population.
Methods
Search strategy and selection criteria
We did a
systematic review and meta-analysis
following the PRISMA and MOOSE
guidelines.16,17
Studies were included in the review
if they had a sample that exclusively
comprised individuals of any age who were
homeless, marginally housed, or seeking
services for homeless people at the time of
assessment (or if there was a clearly
identifiable subgroup of individuals who
were homeless, marginally housed, or seeking
services for homeless people at the time of
assessment and data was able to be extracted
for this subgroup), and if they examined the
prevalence of TBI, the incidence of TBI, or
the association between TBI and one or more
health-related or functioning-related
outcome measures. Our definition of
functioning was deliberately broad to
evaluate the full scope of the effects of
TBI in this population, and was considered
to be any non-health-related outcome measure
or any outcome related to day-to-day
functioning in society (eg, neurocognition
or involvement in the criminal justice
system). Studies were excluded from the
review if they were not published in
English, were not peer-reviewed, or were not
original research studies with unique
observational data (ie, reviews or
meta-analyses).
16.
Moher, D ∙
Liberati, A
∙ Tetzlaff,
J ∙ et al.,
PRISMA Group
Preferred
reporting
items
for
systematic
reviews
and
meta-analyses:
the
PRISMA
statement
BMJ.
2009;
339:1-8
17.
Stroup, DF
∙ Berlin, JA
∙ Morton, SC
∙ et al.
Meta-analysis
of
observational
studies
in
epidemiology:
a
proposal
for
reporting.
Meta-analysis
Of
Observational
Studies
in
Epidemiology
(MOOSE)
group
JAMA.
2000;
283:2008-2012
The decision
to conduct a meta-analysis was made after
doing the literature search to ensure that a
sufficient number of studies were available
that had recorded lifetime prevalence of
TBI. Studies were excluded from the
meta-analysis if they did not have
prevalence data that could be extracted or
obtained through corresponding authors, had
a sample size smaller than 25, or if they
were judged to be from the same study sample
as another study included in the analysis by
consensus of two study authors (JLS and
WJP). For studies that were identifiably
from the same study sample, we included the
study with the largest sample size in the
meta-analysis.
We did a
systematic search without date restrictions
in MEDLINE, Embase, PsycINFO, CINAHL, and
Web of Science using a search strategy
developed in conjunction with a librarian
specialising in systematic review searches.
The search strategy was piloted in MEDLINE
by iteratively adding and refining relevant
search terms and by ensuring that the
included search terms returned studies we
knew to exist on this topic. Our search
strategy was consistent across all
databases, and the strategy used in MEDLINE
(Ovid interface) is reported in the appendix
(p 1). Manual forward and backward
reference searching was done on studies of
particular importance in the opinion of JLS
and WJP and on the previous review on this
topic.15
Searches of all databases and
retrieval of results from each database were
done on Dec 14, 2018, with no date
restrictions.
15.
Topolovec-Vranic,
J ∙ Ennis, N
∙
Colantonio,
A ∙ et al.
Traumatic
brain
injury
among
people
who are
homeless:
a
systematic
review
BMC
Public
Health.
2012;
12,
1059
Screening of
titles and abstracts of all records returned
by the search strategy, screening of full
texts eligible for inclusion, and the risk
of bias assessment for included studies were
independently conducted by two study authors
(JLS and JMS). Inter-rater reliability for
both the title and abstract and full text
screening was calculated using Cohen's κ.
Risk of bias for individual studies was
assessed using the US National Heart, Lung,
and Blood Institute's Quality Assessment
Tool for Observational Cohort and
Cross-Sectional Studies.18
Discrepancies were resolved through
discussion between study authors to reach a
consensus, or with a third study author
(WJP) if necessary.
18.
National
Heart, Lung,
and Blood
Institute
Study
quality
assessment
tools:
quality
assessment
tool for
observational
cohort
and
cross-sectional
studies
https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools
Date:
2014
Date
accessed:
December
14, 2018
The protocol
for our systematic review was registered in
the PROSPERO database (CRD42019119678).
Data analysis
All
variables of interest were independently
extracted by two study authors (JLS and JMS)
using a customised form. The form was
piloted and refined on ten of the studies
selected for inclusion. All extracted
variables are described in the appendix
(p 2).
For studies
included in the meta-analysis, we
quantitatively evaluated several potential
moderators of estimated prevalence of TBI
using meta-regression and subgroup analysis.
First, we evaluated whether the measure of
central tendency of age of the sample
(subsequently referred to as age of the
sample) or the total sample size was
associated with estimated prevalence.
Second, we assessed whether the method of
ascertaining TBI history moderated estimated
prevalence by stratifying TBI ascertainment
methods into five categories: (1) a
non-specific self-report question or series
of questions to ascertain TBI; (2) medical
record; (3) questionnaire or screening tool
specifically designed to ascertain TBI; (4)
the Ohio State University TBI Identification
(OSU TBI-ID) structured interview; and (5)
other ascertainment method. Third, we
evaluated whether studies that used
self-reported loss of consciousness as a
minimum criterion for defining TBI, as
opposed to a more liberal definition (eg,
self-report of a period of being dazed or
confused), were associated with lower
estimated prevalence. Finally, we evaluated
whether the site of participant
recruitment—stratified into studies that
recruited participants from a shelter or
hostel versus studies that recruited
participants from a service or clinic for
homeless individuals—was associated with
different estimates of prevalence.
We did two
separate analyses to evaluate the lifetime
prevalence of TBI. The first aimed to
measure the overall lifetime prevalence of
TBI, encompassing all levels of severity,
and including studies that did not stratify
by severity. The second aimed to measure the
lifetime prevalence of moderate or severe
TBI, encompassing studies that stratified
participants into moderate or severe TBI
categories, studies that examined only
moderate or severe TBI, or studies that
assessed TBI without explicitly defining
severity but which we deemed were
predominantly focused on more significant
brain injury. We deemed that two studies
that did not explicitly evaluate TBI
severity focused predominantly on moderate
or severe TBI; one study assessed “definite
TBI” on the basis of MRI evidence and
persistent sequelae attributable to the
TBI,19
and the other study defined TBI as
brain injury resulting in lasting impairment
or contributing to disability.20
Therefore, we evaluated these two
studies alongside others that explicitly
examined moderate or severe TBI. We used
random-effects models for each analysis to
calculate a pooled estimate of prevalence,
with the Clopper-Pearson method used to
generate 95% CIs for individual studies and
the inverse variance method to weight each
study. We also calculated 95% prediction
intervals (PIs) for our summary estimates to
provide a range for the predicted estimate
of prevalence for new studies.21
19.
Vila-Rodriguez,
F ∙ Panenka,
WJ ∙ Lang,
DJ ∙ et al.
The
hotel
study:
multimorbidity
in a
community
sample
living
in
marginal
housing
Am J
Psychiatry.
2013;
170:1413-1422
20.
Nielssen,
OB ∙ Stone,
W ∙ Jones,
NM ∙ et al.
Characteristics
of
people
attending
psychiatric
clinics
in inner
Sydney
homeless
hostels
Med J
Aust.
2018;
208:169-173
21.
Riley, RD ∙
Higgins, JPT
∙ Deeks, JJ
Interpretation
of
random
effects
meta-analyses
BMJ.
2011;
342:d549
Heterogeneity between studies was quantified
with the I2
statistic.22
For studies that did not report age
of the sample, and for which these data
could not be obtained from the corresponding
author (n=2), we imputed the weighted mean
age of participants from all other studies
that were included in the analysis. We
conducted sensitivity analyses using the
leave-one-out method. We evaluated
small-study effects visually with a funnel
plot and statistically with Egger's
test.23
22.
Higgins,
JPT ∙
Thompson, SG
∙ Deeks, JJ
∙ et al.
Measuring
inconsistency
in
meta-analyses
BMJ.
2003;
327:557-560
23.
Egger, M ∙
Davey Smith,
G ∙
Schneider, M
∙ et al.
Bias
in
meta-analysis
detected
by a
simple,
graphical
test
BMJ.
1997;
315:629-634
Finally, we
used subgroup analysis and meta-regression
to evaluate moderators of individual study
estimates of the lifetime prevalence of TBI.
We used univariable meta-regression to
evaluate unadjusted effects in the analyses
of lifetime prevalence and the lifetime
prevalence of moderate or severe TBI, and we
included all potential moderators, for which
appropriate data were available, in a
multivariable meta-regression to evaluate
adjusted effects in the analysis of lifetime
prevalence. We used mixed effects models for
all meta-regression analyses.
All
statistical analyses were performed in R
(version 3.5.1) with the packages meta
(version 4.9-4) and metafor (version
2.0-0).24–26
24.
R Core Team
R:
a
language
and
environment
for
statistical
computing
R
Foundation
for
Statistical
Computing,
Vienna,
Austria,
2019
25.
Schwarzer,
G
meta:
an R
package
for
meta-analysis
R
News.
2007;
7:40-45
26.
Viechtbauer,
W
Conducting
meta-analyses
in R
with the
metaphor
package
J Stat
Softw.
2010;
36:1-48
Role of the funding source
The funder
of the study had no role in study design,
data collection, data analysis, data
interpretation, or writing of the report.
The corresponding author had full access to
all the data in the study and had final
responsibility for the decision to submit
for publication.
Results
Our database
searches identified 463 potentially eligible
studies. After removal of duplicates, 260 study
titles and abstracts were screened (figure 1).
We assessed 51 full text articles for
eligibility, of which 13 were excluded from the
systematic review (appendix p
1) and an additional 16 were excluded
from the meta-analysis. There was a high
inter-rater reliability for screening titles and
abstracts (κ=0·95) and full texts (κ=0·96).
30188-4/asset/6b3aaa8b-87cb-4726-a213-e4157b682389/main.assets/gr1.gif)
Figure
1 Study
selection
38 studies were
included in the systematic review (table
1).19,20,27–62
The included studies were published
between 1995 and 2018, and recruited
participants from Australia, Canada, Japan,
South Korea, the UK, and the USA. The
predominant recruitment settings were through
homeless shelters or hostels (18 studies) and
services or clinics that serve homeless
populations (16 studies). Six (16%) of 38
studies were conducted in populations of
military service members who were homeless or
seeking services for homeless people, and the
remainder of studies recruited participants from
civilian populations. Of the 38 studies included
in the systematic review, we included 22 in the
meta-analysis (figure 1). 18 (82%) of 22
studies (n=9702) assessed the lifetime
prevalence of TBI, and nine (41%, n=5787)
assessed the lifetime prevalence of moderate or
severe TBI.
19.
Vila-Rodriguez,
F ∙ Panenka, WJ
∙ Lang, DJ ∙ et
al.
The
hotel study:
multimorbidity
in a
community
sample
living in
marginal
housing
Am J
Psychiatry.
2013;
170:1413-1422
20.
Nielssen, OB ∙
Stone, W ∙
Jones, NM ∙ et
al.
Characteristics
of people
attending
psychiatric
clinics in
inner Sydney
homeless
hostels
Med J
Aust.
2018;
208:169-173
27.
Andersen, J ∙
Kot, N ∙ Ennis,
N ∙ et al.
Traumatic
brain injury
and
cognitive
impairment
in men who
are
homeless
Disabil
Rehabil.
2014;
36:2210-2215
28.
Bacciardi, S ∙
Maremmani, AG ∙
Nikoo, N ∙ et
al.
Is
bipolar
disorder
associated
with
tramautic
brain injury
in the
homeless?
Riv
Psichiatr.
2017;
52:40-46
29.
Barnes, SM ∙
Russell, LM ∙
Hostetter, TA ∙
et al.
Characteristics
of traumatic
brain
injuries
sustained
among
veterans
seeking
homeless
services
J Health
Care Poor
Underserved.
2015;
26:92-105
30.
Bremner, AJ ∙
Duke, PJ ∙
Nelson, HE ∙ et
al.
Cognitive
function and
duration of
rooflessness
in entrants
to a hostel
for homeless
men
Br J
Psychiatry.
1996;
169:434-439
31.
Brenner, LA ∙
Hostetter, TA ∙
Barnes, SM ∙ et
al.
Traumatic
brain
injury,
psychiatric
diagnoses,
and suicide
risk among
Veterans
seeking
services
related to
homelessness
Brain
Inj.
2017;
31:1731-1735
32.
Brown, RT ∙
Kiely, DK ∙
Bharel, M ∙ et
al.
Factors
associated
with
geriatric
syndromes in
older
homeless
adults
J Health
Care Poor
Underserved.
2013;
24:456-468
33.
Bymaster, A ∙
Chung, J ∙
Banke, A ∙ et
al.
A
pediatric
profile of a
homeless
patient in
San Jose,
California
J Health
Care Poor
Underserved.
2017;
28:582-595
34.
Cotman, A ∙
Sandman, C
Cognitive
deficits and
their
remediation
in the
homeless
J Cogn
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|---|---|---|---|---|---|---|---|---|---|---|
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Canada | Cross-sectional | Shelter for homeless men | 34 | 58·8 | 0/34 | 12/34 (35·3%) | 11/34 (32·4%) | . | Questionnaire or screening tool: Brain Injury Screening Questionnaire |
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Canada | Cross-sectional | Community agencies that serve homeless individuals (shelters, drop-in centres, outreach teams, inpatient programmes, and criminal justice programmes) | 416 | 39·9 | 117/416 (28·1%) | 277/416 (66·6%) | 108/198 (54·5%)§ | . | Single question or series of questions: “Have you ever had an injury to the head which knocked you out or at least left you dazed, confused, or disoriented?” |
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services
are
delivered?
Can
J
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Health.
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Canada | Cross-sectional | Clients seeking support from an Assertive Community Treatment Team in a downtown urban setting | 48 | 43·4 | 15/48 (31·3%) | 27/48 (56·3%) | . | . | Structured interview: OSU TBI-ID |
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USA | Cross-sectional | Homeless shelters and domestic violence facility | 282 | 34·8 | 248/282 (87·9%) | 69/282 (24·5%) | . | . | Questionnaire or screening tool: HELPS screening tool |
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Canada | Cross-sectional | Shelters and meal programmes | 904 | 37·4 | 303/904 (33·5%) | 475/904 (52·5%) | 109/904 (12·1%) | . | Single question or series of questions: “Have you ever had an injury to the head which knocked you out or at least left you dazed, confused, or disoriented?”; additional injury details for up to three injuries were collected |
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Canada | Cross-sectional | Community agencies that serve homeless individuals (shelters, drop-in centres, outreach teams, inpatient programmes, and criminal justice programmes) in five Canadian cities | 2255 | 40·9 | 730/2255 (32·4%) | 1475/2255 (65·4%) | . | . | Single question or series of questions: “Have you ever had an injury to the head which knocked you out or at least left you dazed, confused, or disoriented?” |
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USA | Retrospective case-control | VA North Texas Health Care System | 2205 | 53·6 | 121/2205 (5·5%) | . | . | 0·5% over 1 year | Medical record: ICD-9 codes |
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UK | Cross-sectional | Dry hostels, wet hostels, and day centres for homeless individuals | 100 | 32·7 | 25/100 (25·0%) | 48/100 (48·0%) | 12/65 (18·5%) | . | Single question or series of questions: “Have you ever had an injury to the head which knocked you out or at least left you dazed, confused, or disoriented?”, with additional questions regarding the number of injuries, LOC and whether participants went to the hospital for the first three injuries |
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USA | Cross-sectional | Metropolitan VA hospital | 678 | 51·9 | 36/678 (5·3%) | 285/313 (91·1%) | . | . | Structured interview and questionnaire or screening tool: OSU TBI-ID and TBI-4¶ |
| Schmitt et al
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Canada | Cross-sectional | Single-room occupancy hotel rooms and downtown community court | 283 | 43·5 | 47/205 (22·9%) | 100/283 (35·3%) | 49/283 (17·3%) | . | Single question or series of questions: “Have you ever had a serious head/face injury?”, with additional questions regarding LOC, confusion, or memory loss post injury |
| Solliday-McRoy et al
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USA | Cross-sectional | Homeless shelter | 90 | 41 | 0/90 | 43/90 (47·8%) | 16/90 (17·8%) | . | Single or series of questions: specific questions NR |
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Canada | Cross-sectional | Shelters, homeless outreach services, and streets in three Canadian cities | 500 | 38 | 200/500 (40·0%) | 318/500 (63·6%) | . | . | Single question or series of questions: “Have you ever had an injury to the head which knocked you out or at least left you dazed, confused, or disoriented?'” |
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Canada | Cross-sectional | Community agencies that serve homeless individuals (shelters, drop-in centres, outreach teams, inpatient programmes, and criminal justice programmes) in five Canadian cities | 1500 | 41·1 | 477/1500 (31·8%) | . | 688/1500 (45·9%) | . | Single question or series of questions: specific questions NR |
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Canada | Retrospective cohort | Wet shelter programme, hostel for homeless individuals, and three low-income housing sites | 170 | 43·7 | 0/170 | . | . | 28·8% (participants in wet shelters); 3·3% (participants in hostels); and 5·1% (participants in low-income housing) over 1 year | Medical record: broad criteria to capture “head injury” |
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Table 1
Summary of included studies
TBI=traumatic brain injury.
VA=US Department of Veterans
Affairs. OSU TBI-ID=Ohio State
TBI Identification method.
NR=not reported. LOC=loss of
consciousness. ICD=International
Classification of Diseases.
*
Measure
of central tendency
(mean or median), unless
otherwise stated.
†
Included in
meta-analysis of
lifetime prevalence.
‡
Included in
meta-analysis of
lifetime prevalence of
moderate or severe TBI.
§
218
(52·4%) of 416
participants were
missing data on severe
TBI.
¶
Prevalence estimate from
the OSU TBI-ID (n=313)
used in meta-analysis.
The risk of bias
assessment for all studies included in the
systematic review is shown in the appendix (pp
2, 3). In general, studies had a clear
research objective, recruited participants from
similar populations, and clearly described
dependent variables. However, 17 (45%) of 38
studies did not provide a clear definition of
homelessness or marginal housing, and 23 (61%)
did not report whether the participation rate of
eligible persons was more than 50%. Of note, 20
(53%) of 38 studies did not clearly describe the
specific definition used to categorise
participants as having TBI. Studies were
generally comprised of predominantly male
samples, and eight studies were comprised of
exclusively male samples.
The overall
pooled estimate of the lifetime prevalence of
TBI was 53·1% (95% CI 46·4–59·7, 95% PI
25·9–78·6; figure 2). There was a
significant amount of heterogeneity between
studies (I2=97%, p<0·0001).
The funnel plot is reported in the appendix (p
4) and did not show evidence of
small-study effects, which was supported by
Egger's test (p=0·96). The results of the
leave-one-out sensitivity analyses are reported
in the appendix (p
5), and show that no single study, nor
the studies for which we imputed mean age, had a
disproportionate effect on the pooled estimate
of prevalence of TBI.
30188-4/asset/33a780ad-7fce-49ff-8d65-0aa2cf99c771/main.assets/gr2_lrg.jpg)
Figure
2 Forest
plots of prevalence estimates
for any severity of TBI and for
moderate or severe TBI
The results from
our univariable and multivariable
meta-regression analyses are reported in table 2,
with raw coefficients reported in the appendix (p
6). The overall multivariable
meta-regression model was significant and
accounted for 30·0% of the heterogeneity
(Q5=27·20, p<0·0001,
R2=0·300). The age of the
study sample (p=0·045), total sample size
(p=0·047), and using the OSU TBI-ID structured
interview (vs a single question or series
of questions) to ascertain history of TBI
(p=0·0035) were significantly associated with
higher estimated prevalence. Studies that used
other screening tools (HELPS or BISQ) to
ascertain history of TBI (p=0·11) and the site
of study recruitment (p=0·85) were not
significantly associated with estimated
prevalence in the meta-regression, although the
sample size for each predictor was relatively
small. Three studies reported both an overall
estimate of prevalence and a subgroup of
individuals who reported loss of consciousness
after injury.33,35,53
On average, 43·4% reported loss of
consciousness (range 32·2–58·0), compared with
the total 56·0% (range 35·3–76·4) who reported
TBI across those three studies with a more
inclusive definition (ie, self-reporting a
period of being dazed, confused, or experiencing
memory loss). Individual study and pooled
estimates of lifetime TBI prevalence stratified
by TBI ascertainment method are shown in the appendix (p
7). Heterogeneity among studies that
ascertained history of TBI using OSU TBI-ID
structured interviews (I2=95%)
and other screening tools
(I2=94%) was high, although it
was lower than the heterogeneity observed across
all studies (I2=97%).
33.
Bymaster, A ∙
Chung, J ∙
Banke, A ∙ et
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Gerber, GJ ∙
Nir, P
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injury in
persons with
serious
mental
illness who
have a
history of
chronic
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could this
impact how
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Commun Ment
Health.
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53.
Schmitt, T ∙
Thornton, AE ∙
Rawtaer, I ∙ et
al.
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brain injury
in a
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| Studies | Participants | Estimated prevalence, % (95% CI) | Heterogeneity | Change in estimated prevalence from univariable meta-regression analyses* | Change in estimated prevalence from multivariable meta-regression analysis* | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| I2 | p value | Change, % (95% CI) | p value | Change, % (95% CI) | p value | |||||
| Measure of central tendency of age for the study sample | 18 | 9702 | 52·1% (46·4–59·7) | 97% | <0·0001 | 1·5% (−4·7 × 10−2 to 3·1) | 0·058 | 1·6% (2·7 × 10−2 to 3·2) | 0·045 | |
| Sample size | 18 | 9702 | 52·1% (46·4–59·7) | 97% | <0·0001 | 5·3 × 10−3% (−1·6 × 10−2 to 2·6 × 10−2) | 0·49 | 1·8 × 10−2% (3·6 × 10−4 to 3·6 × 10−2) | 0·047 | |
| Site of study recruitment | ||||||||||
| Service or clinic | 6 | 2855 | 64·7% (48·2–78·3) | 95% | <0·0001 | Reference | . | Reference | . | |
| Shelter or hostel | 12 | 6847 | 47·4% (41·1–53·7) | 95% | <0·0001 | −39·4% (−66·7 to −12·1) | 0·0047 | 3·6% (−31·4 to 38·1) | 0·85 | |
| TBI ascertainment method | ||||||||||
| Single question or series of questions | 13 | 8821 | 50·1% (43·7–56·5) | 97% | <0·0001 | −25·0% (−57·6 to 7·7) | 0·13 | Reference | . | |
| Other screening tool (HELPS or BISQ) | 2 | 393 | 33·8% (17·1–55·9) | 94% | <0·0001 | −47·8% (−90·8 to −4·8) | 0·029 | −32·7% (−73·1 to 7·6) | 0·11 | |
| OSU TBI-ID structured interview | 3 | 488 | 78·0% (53·4–91·6) | 95% | <0·0001 | 73·6% (37·4 to 100·0) | <0·0001 | 67·9% (22·3 to 100·0) | 0·0035 | |
Table 2
Meta-regression results
evaluating potential moderators
of estimated lifetime TBI
prevalence
LOC=loss of consciousness.
TBI=traumatic brain injury. OSU
TBI-ID=Ohio State TBI
Identification method.
*
For a
one-unit change in the
predictor variable.
The pooled
estimate of the lifetime prevalence of moderate
or severe TBI was 22·5% (95% CI 13·5–35·0, 95%
PI 3·1–72·3; figure 2). There was high
heterogeneity between studies
(I2=99%, p<0·0001). The
funnel plot is reported in the appendix (p
8) and did not show evidence of
small-study effects upon visual inspection;
Egger's test showed no asymmetry (p=0·56). The
leave-one-out sensitivity analyses are reported
in the appendix (p
9), and show that no single study, nor
the studies that did not explicitly evaluate
severity but which we deemed to be focused
predominantly on moderate or severe TBI, had a
disproportionate effect on the pooled estimate
of lifetime prevalence of moderate or severe
TBI. None of the moderators (as previously
described for overall lifetime prevalence of
TBI) were statistically significantly associated
with estimated prevalence of moderate or severe
TBI in univariable meta-regression analyses.
In this review,
28 (74%) of 38 studies assessed the association
between a history of TBI and health-related or
functioning-related outcomes. A summary of
results is reported in the panel, and a study-level
breakdown of results is presented in the appendix (pp
9–12). The association between TBI and
many outcome measures was equivocal, whereby
findings were either mixed or the outcome was
evaluated by only a small number of studies.
However, despite the heterogeneity in study
methodology and outcomes assessed, history of
TBI was consistently associated with poorer
self-reported physical39,53,58
and mental health,39,53,58
increased health service use43,58,60
and criminal justice involvement,43,53,58–60
and younger age at first experience of
homelessness39,43,58
in all studies that evaluated TBI and
these outcomes. Furthermore, history of TBI was
associated with suicidal ideation and higher
suicide risk31,43,51,60
in four of five studies53
that evaluated suicidality, and
self-reported memory concerns35,38,43,53,61
in five of six studies34
that evaluated memory concerns. The most
common mechanism of injury was assault across
all five studies that evaluated mechanism of
injury.29,33,35,53,59
Age at first TBI ranged from 15 years to
19·9 years, and we calculated a weighted mean
age of first TBI of 15·8 years. In one large
marginally housed cohort who underwent MRI
scans, 28·0% of participants had incidental
neuroimaging findings (eg, aneurysms or
infarcts), with 6·9% in a largely overlapping
sample showing evidence of previous brain
trauma.19,53
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Chiu, S ∙ et al.
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Gerber,
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Bennett,
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Grubenhoff,
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bipolar disorder
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manic or
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Schuler,
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Gozdzik,
A
∙
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traumatic
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and
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adults
with
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87:53-60
60.
Topolovec-Vranic,
J
∙
Schuler,
A
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Gozdzik,
A
∙
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and a history of
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study59
39.
Hwang,
SW
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Colantonio,
A
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Chiu,
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Howatt,
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Associated with lower
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and not
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Associated with
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Gerber,
GJ
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35.
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Gerber,
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who
have
a
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this
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are
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Schmitt,
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55.
Song,
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Nikoo,
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Ennis,
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Howatt,
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et
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homeless
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Associated with alcohol
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Hwang,
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Chiu,
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traumatic
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on
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of
homeless
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43.
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Harpin,
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Grubenhoff,
JA
∙
et
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104:1986-1992
53.
Schmitt,
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Thornton,
AE
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Rawtaer,
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et
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Palepu,
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et
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and
victimization
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burden
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traumatic
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injury
and
comorbidities
amongst
homeless
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J
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35.
Gargaro,
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∙
Gerber,
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∙
Nir,
P
Brain
injury
in
persons
with
serious
mental
illness
who
have
a
history
of
chronic
homelessness:
could
this
impact
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are
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Can
J
Commun
Ment
Health.
2016;
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55.
Song,
MJ
∙
Nikoo,
M
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Choi,
F
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et
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trauma
and
lifetime
traumatic
brain
injury
among
individuals
who
are
homeless
J
Head
Trauma
Rehabil.
2018;
33:185-190
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Associated with mood
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features in one
study60
53.
Schmitt,
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Thornton,
AE
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Rawtaer,
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and diagnosed
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Associated with trouble
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behaviour in one
study35
35.
Gargaro,
J
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Gerber,
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P
Brain
injury
in
persons
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serious
mental
illness
who
have
a
history
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Associated with
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35.
Gargaro,
J
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Gerber,
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53.
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Mackelprang,
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35.
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Temporal relationship to homelessness
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their first experience
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29.
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Mackelprang,
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Grubenhoff,
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Mackelprang,
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Grubenhoff,
JA
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Associated with a
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childhood physical
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55.
Song,
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Associated with a
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Grubenhoff,
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et
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homeless
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Associated with lower
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educational attainment
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and a history of
special education in one
study;43
not associated
with education in two
studies53,59
43.
Mackelprang,
JL
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Harpin,
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Grubenhoff,
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et
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Associated with
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associated with
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58.
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homeless
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Associated with higher
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associated with
outpatient days in the
previous 6 months in one
study60
43.
Mackelprang,
JL
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Harpin,
SB
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Grubenhoff,
JA
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et
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traumatic
brain
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injury
Am
J
Public
Health.
2014;
104:1986-1992
53.
Schmitt,
T
∙
Thornton,
AE
∙
Rawtaer,
I
∙
et
al.
Traumatic
brain
injury
in
a
community-based
cohort
of
homeless
and
vulnerably
housed
individuals
J
Neurotrauma.
2017;
34:3301-3310
58.
To,
MJ
∙
O'Brien,
K
∙
Palepu,
A
∙
et
al.
Healthcare
utilization,
legal
incidents,
and
victimization
following
traumatic
brain
injury
in
homeless
and
vulnerably
housed
individuals:
a
prospective
cohort
study
J
Head
Trauma
Rehabil.
2015;
30:270-276
59.
Topolovec-Vranic,
J
∙
Ennis,
N
∙
Howatt,
M
∙
et
al.
Traumatic
brain
injury
among
men
in
an
urban
homeless
shelter:
observational
study
of
rates
and
mechanisms
of
injury
CMAJ
Open.
2014;
2:e69-e76
60.
Topolovec-Vranic,
J
∙
Schuler,
A
∙
Gozdzik,
A
∙
et
al.
The
high
burden
of
traumatic
brain
injury
and
comorbidities
amongst
homeless
adults
with
mental
illness
J
Psychiatr
Res.
2017;
87:53-60
•
Associated with being a
victim of physical or
sexual assault in two
studies43,58
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
58.
To,
MJ
∙
O'Brien,
K
∙
Palepu,
A
∙
et
al.
Healthcare
utilization,
legal
incidents,
and
victimization
following
traumatic
brain
injury
in
homeless
and
vulnerably
housed
individuals:
a
prospective
cohort
study
J
Head
Trauma
Rehabil.
2015;
30:270-276
•
Associated with a
parental history of
substance abuse in one
study59
59.
Topolovec-Vranic,
J
∙
Ennis,
N
∙
Howatt,
M
∙
et
al.
Traumatic
brain
injury
among
men
in
an
urban
homeless
shelter:
observational
study
of
rates
and
mechanisms
of
injury
CMAJ
Open.
2014;
2:e69-e76
•
Associated with
so-called survival sex
during homelessness in
one study43
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
•
Associated with a
history of foster care
in one study43
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
•
Associated with a higher
number of homeless
episodes or a longer
lifetime duration of
homelessness in two
studies,43,58
and not
associated with lifetime
duration of homelessness
or marginal housing in
two studies53,59
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
58.
To,
MJ
∙
O'Brien,
K
∙
Palepu,
A
∙
et
al.
Healthcare
utilization,
legal
incidents,
and
victimization
following
traumatic
brain
injury
in
homeless
and
vulnerably
housed
individuals:
a
prospective
cohort
study
J
Head
Trauma
Rehabil.
2015;
30:270-276
53.
Schmitt,
T
∙
Thornton,
AE
∙
Rawtaer,
I
∙
et
al.
Traumatic
brain
injury
in
a
community-based
cohort
of
homeless
and
vulnerably
housed
individuals
J
Neurotrauma.
2017;
34:3301-3310
59.
Topolovec-Vranic,
J
∙
Ennis,
N
∙
Howatt,
M
∙
et
al.
Traumatic
brain
injury
among
men
in
an
urban
homeless
shelter:
observational
study
of
rates
and
mechanisms
of
injury
CMAJ
Open.
2014;
2:e69-e76
•
Associated with military
service in one
study43
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
•
Not
associated with having a
place to go when sick or
in need of health advice
in one study60
60.
Topolovec-Vranic,
J
∙
Schuler,
A
∙
Gozdzik,
A
∙
et
al.
The
high
burden
of
traumatic
brain
injury
and
comorbidities
amongst
homeless
adults
with
mental
illness
J
Psychiatr
Res.
2017;
87:53-60
•
Not
associated with marital
status in one study43
43.
Mackelprang,
JL
∙
Harpin,
SB
∙
Grubenhoff,
JA
∙
et
al.
Adverse
outcomes
among
homeless
adolescents
and
young
adults
who
report
a
history
of
traumatic
brain
injury
Am
J
Public
Health.
2014;
104:1986-1992
•
Not
associated with
screening positive for
homelessness in veterans
in one study46
46.
Montgomery,
AE
∙
Dichter,
ME
∙
Thomasson,
AM
∙
et
al.
Disparities
in
housing
status
among
veterans
with
general
medical,
cognitive,
and
behavioral
health
conditions
Psychiatr
Serv.
2015;
66:317-320
Only five
studies included in this review assessed
incident TBI, precluding a methodologically
robust meta-analysis of the incidence of TBI in
this population. Estimated incidence of TBI in
homeless and marginally housed individuals
varied considerably between studies and ranged
from 0·5% over 1 year42
to 28% over 1 year.57
Although we did not quantitatively
assess moderators of these estimates, TBI
ascertainment method appeared to be associated
with estimated incidence. For example, Nikoo and
colleagues48
did a comprehensive baseline interview
with each participant and assessed incident TBI
at yearly follow-up interviews, and found that
17·1–19·4% of participants sustained TBI per
year.48
By contrast, LePage and colleagues42
and McMillan and colleagues45
used ICD-9 codes, ICD-10 codes, or both
to ascertain TBI.42,45
LePage and colleagues found that 0·5% of
participants sustained TBI over 1 year, and
McMillan and colleagues found that 13·5% of
participants sustained TBI over the 30-year
study period (approximately 0·5% per year). A
study-level summary of results from studies
evaluating incidence of TBI is presented in the
appendix (p
13). Homelessness was associated with a
higher incidence of TBI in comparison with
non-homeless control groups.42,44,45,57
Similarly, residential instability was
associated with a higher incidence of TBI.48
Lifetime history of TBI, receiving a TBI
in the previous year, mental health diagnoses
and poorer mental health, drug and alcohol
misuse, and younger age were also associated
with incident TBI over a 1-year period.48,57
42.
LePage, JP ∙
Bradshaw, LD ∙
Cipher, DJ ∙ et
al.
The
effects of
homelessness
on Veterans'
health care
service use:
an
evaluation
of
independence
from
comorbidities
Public
Health.
2014;
128:985-992
57.
Svoboda, T ∙
Ramsay, JT
High
rates of
head injury
among
homeless and
low-income
housed men:
a
retrospective
cohort
study
Emerg Med
J.
2014;
31:571-575
48.
Nikoo, M ∙
Gadermann, A ∙
To, MJ ∙ et al.
Incidence
and
associated
risk factors
of traumatic
brain injury
in a cohort
of homeless
and
vulnerably
housed
adults in 3
Canadian
cities
J Head
Trauma
Rehabil.
2017;
32:E19-E26
48.
Nikoo, M ∙
Gadermann, A ∙
To, MJ ∙ et al.
Incidence
and
associated
risk factors
of traumatic
brain injury
in a cohort
of homeless
and
vulnerably
housed
adults in 3
Canadian
cities
J Head
Trauma
Rehabil.
2017;
32:E19-E26
42.
LePage, JP ∙
Bradshaw, LD ∙
Cipher, DJ ∙ et
al.
The
effects of
homelessness
on Veterans'
health care
service use:
an
evaluation
of
independence
from
comorbidities
Public
Health.
2014;
128:985-992
45.
McMillan, TM ∙
Laurie, M ∙
Oddy, M ∙ et al.
Head
injury and
mortality in
the
homeless
J
Neurotrauma.
2015;
32:116-119
42.
LePage, JP ∙
Bradshaw, LD ∙
Cipher, DJ ∙ et
al.
The
effects of
homelessness
on Veterans'
health care
service use:
an
evaluation
of
independence
from
comorbidities
Public
Health.
2014;
128:985-992
45.
McMillan, TM ∙
Laurie, M ∙
Oddy, M ∙ et al.
Head
injury and
mortality in
the
homeless
J
Neurotrauma.
2015;
32:116-119
42.
LePage, JP ∙
Bradshaw, LD ∙
Cipher, DJ ∙ et
al.
The
effects of
homelessness
on Veterans'
health care
service use:
an
evaluation
of
independence
from
comorbidities
Public
Health.
2014;
128:985-992
44.
McCormick, B ∙
White, J
Hospital
care and
costs for
homeless
people
Clin Med
(Lond).
2016;
16:506-510
45.
McMillan, TM ∙
Laurie, M ∙
Oddy, M ∙ et al.
Head
injury and
mortality in
the
homeless
J
Neurotrauma.
2015;
32:116-119
57.
Svoboda, T ∙
Ramsay, JT
High
rates of
head injury
among
homeless and
low-income
housed men:
a
retrospective
cohort
study
Emerg Med
J.
2014;
31:571-575
48.
Nikoo, M ∙
Gadermann, A ∙
To, MJ ∙ et al.
Incidence
and
associated
risk factors
of traumatic
brain injury
in a cohort
of homeless
and
vulnerably
housed
adults in 3
Canadian
cities
J Head
Trauma
Rehabil.
2017;
32:E19-E26
48.
Nikoo, M ∙
Gadermann, A ∙
To, MJ ∙ et al.
Incidence
and
associated
risk factors
of traumatic
brain injury
in a cohort
of homeless
and
vulnerably
housed
adults in 3
Canadian
cities
J Head
Trauma
Rehabil.
2017;
32:E19-E26
57.
Svoboda, T ∙
Ramsay, JT
High
rates of
head injury
among
homeless and
low-income
housed men:
a
retrospective
cohort
study
Emerg Med
J.
2014;
31:571-575
Discussion
The results of
our systematic review and meta-analysis suggest
that more than half of homeless and marginally
housed individuals have a lifetime history of
TBI, and that almost a quarter have a history of
moderate or severe TBI. Thus, the lifetime
prevalence of TBI in homeless and marginally
housed individuals is between 2·5-times and
4·0-times higher than estimates in the general
population.8,11
Moreover, the lifetime prevalence of
moderate or severe TBI in this population is
nearly ten-times higher than estimates in the
general population.8
We also found that TBI was associated
with increased suicidal ideation and suicide
risk, poorer self-reported physical and mental
health, and increased health service and
criminal justice system involvement. However,
heterogeneity across estimates limits our
ability to establish the true prevalence of TBI
in this population.
8.
Corrigan, JD ∙
Yang, J ∙
Singichetti, B ∙
et al.
Lifetime
prevalence
of traumatic
brain injury
with loss of
consciousness
Inj
Prev.
2018;
24:396-404
11.
Frost, RB ∙
Farrer, TJ ∙
Primosch, M ∙ et
al.
Prevalence
of traumatic
brain injury
in the
general
adult
population:
a
meta-analysis
Neuroepidemiology.
2013;
40:154-159
8.
Corrigan, JD ∙
Yang, J ∙
Singichetti, B ∙
et al.
Lifetime
prevalence
of traumatic
brain injury
with loss of
consciousness
Inj
Prev.
2018;
24:396-404
We identified
high statistical heterogeneity and considerable
methodological limitations across many of the
included studies, which hinders a clear
understanding of the magnitude of the impact of
TBI in this population. This heterogeneity can
be attributed in part to the age of the study
sample, because study samples with a higher
proportion of older individuals evaluate
individuals with a longer time at risk of TBI.
This heterogeneity is also explained in part by
study design factors, such as the tool used to
ascertain TBI history, which reflects that
standardised and reproducible research methods
were not always used in previous studies on this
topic. Three studies in our review had
identifiable subgroups defined only by loss of
consciousness. These studies suggest that using
only loss of consciousness as a screening
criterion might result in lower estimated
prevalence than the standard WHO criteria, which
also include confusion and memory loss. In the
general population, excluding individuals with a
head injury and alteration (but not loss) of
consciousness would miss approximately 80% of
all injuries considered to be TBIs by commonly
used definitions.5,63,64
Notably, the use of OSU TBI-ID to
ascertain TBI history was associated with an
estimated prevalence that was nearly 30% higher
than in studies that used a single question.
Although they have inherent limitations,
clinical interviews such as the OSU TBI-ID are
considered to be the preferred method for
ascertaining TBI history.65
Clinical interviews also allow a trained
researcher to use an approach tailored to the
study population to obtain the level of detail
required for an expert assessment of the
evidence. Thus, ascertainment method might
represent one of the most important design
considerations in studies evaluating history of
TBI. Consequently, our summary estimate of
prevalence in this population is limited by
inadequate ascertainment methods that appear to
underestimate the prevalence of TBI in this
population. If prevalence estimates ascertained
through structured interviews represent the most
accurate estimate of prevalence, our pooled
estimate of prevalence might be a considerable
underestimate of the true prevalence of TBI in
this population.
5.
Maas, AIR ∙
Menon, DK ∙
Adelson, PD ∙ et
al.
Traumatic
brain
injury:
integrated
approaches
to improve
prevention,
clinical
care, and
research
Lancet
Neurol.
2017;
16:987-1048
63.
Menon, DK ∙
Schwab, K ∙
Wright, DW ∙ et
al.
Position
statement:
definition
of traumatic
brain
injury
Arch Phys
Med
Rehabil.
2010;
91:1637-1640
64.
American
Congress of
Rehabilitation
Medicine
Definition
of mild
traumatic
brain
injury
J Head
Trauma
Rehabil.
1993;
8:86-87
65.
Walker, WC ∙
Cifu, DX ∙
Hudak, AM ∙ et
al.
Structured
interview
for mild
traumatic
brain injury
after
military
blast:
inter-rater
agreement
and
development
of
diagnostic
algorithm
J
Neurotrauma.
2015;
32:464-473
Despite
considerable statistical and methodological
heterogeneity between studies, we found that a
history of TBI is associated with various
aspects of poor health and functioning.
Additionally, several characteristics of
homeless and marginally housed populations (eg,
residential instability or substance use) were
associated with sustaining TBI. Some
relationships might be bidirectional: for
example, TBI could increase the risk for
homelessness, and homelessness could increase
the risk for incident TBI. Establishing whether
TBI is a risk factor for poor outcomes (eg,
homelessness or serious health conditions) will
be important to understand and address the
impact of TBI in this population.
Our results
suggest that physicians and care providers
working with homeless and marginally housed
populations should have an increased awareness
of TBI. Previous studies have shown that
homeless and marginally housed individuals have
a frequency of actionable incidental findings on
brain MRI that substantially exceed that
expected of the general population.19
For example, Vila-Rodriguez and
colleagues19
reported that the prevalence of
aneurysms was 8·6% and of brain infarcts was 11%
in homeless and marginally housed individuals.
By contrast, the expected rates in similarly
aged samples from the general population are
less than 1% for aneurysms and less than 3% for
brain infarcts.66
In an overlapping sample, Schmitt and
colleagues53
reported visible encephalomalacia on
neuroimaging that was deemed likely to be caused
by traumatic injury in 6·9% of the cohort, and
found that evidence of trauma on neuroimaging
was associated with poorer cognition and
executive functioning in this population.53
Clinicians might therefore consider
lowering the threshold for referral to
neuroimaging specialists after head injury in
homeless and marginally housed patients, because
depending on the resources available, an
assessment that complements self-reporting might
be indicated. Confirmation of structural brain
damage caused by TBI might facilitate triage and
referral to specialised services, such as
cognitive rehabilitation, which could improve
functional outcomes.67,68
Furthermore, imaging findings might
positively inform the patient–caregiver
relationship (eg, by increasing understanding of
challenging behaviours that might be
attributable to damage visible on neuroimaging).
19.
Vila-Rodriguez,
F ∙ Panenka, WJ
∙ Lang, DJ ∙ et
al.
The
hotel study:
multimorbidity
in a
community
sample
living in
marginal
housing
Am J
Psychiatry.
2013;
170:1413-1422
19.
Vila-Rodriguez,
F ∙ Panenka, WJ
∙ Lang, DJ ∙ et
al.
The
hotel study:
multimorbidity
in a
community
sample
living in
marginal
housing
Am J
Psychiatry.
2013;
170:1413-1422
66.
Morris, Z ∙
Whiteley, WN ∙
Longstreth, WT ∙
et al.
Incidental
findings on
brain
magnetic
resonance
imaging:
systematic
review and
meta-analysis
BMJ.
2009;
339:1-7
53.
Schmitt, T ∙
Thornton, AE ∙
Rawtaer, I ∙ et
al.
Traumatic
brain injury
in a
community-based
cohort of
homeless and
vulnerably
housed
individuals
J
Neurotrauma.
2017;
34:3301-3310
53.
Schmitt, T ∙
Thornton, AE ∙
Rawtaer, I ∙ et
al.
Traumatic
brain injury
in a
community-based
cohort of
homeless and
vulnerably
housed
individuals
J
Neurotrauma.
2017;
34:3301-3310
67.
Hallock, H ∙
Collins, D ∙
Lampit, A ∙ et
al.
Cognitive
training for
post-acute
traumatic
brain
injury: a
systematic
review and
meta-analysis
Front Hum
Neurosci.
2016;
10:537
68.
Cicerone, KD ∙
Langenbahn, DM ∙
Braden, C ∙ et
al.
Evidence-based
cognitive
rehabilitation:
updated
review of
the
literature
from 2003
through
2008
Arch Phys
Med
Rehabil.
2011;
92:519-530
To our
knowledge, this is the first study to
quantitatively evaluate the lifetime prevalence
of TBI and to comprehensively summarise the
associations between TBI and health-related or
functioning-related outcomes in homeless and
marginally housed individuals. However, our
study has some limitations. Firstly, the
included studies were almost exclusively
retrospective in design, which precludes
interpretation about the directionality of the
relationships. Future prospective studies are
needed in order to adequately evaluate, for
example, whether TBI leads to substance use or
homelessness, or whether factors such as
substance use or homelessness lead to TBI.
Secondly, we limited our search to peer-reviewed
publications and elected not to search the
so-called grey literature. In the screening
process for this study, we encountered several
theses and book chapters; however, we elected to
exclude these in order to limit our results to
only peer-reviewed studies.
TBI is prevalent
among homeless and marginally housed individuals
and might be a common factor that contributes to
poorer health and functioning than in the
general population. Primary care providers and
those working with this group should be aware of
the prevalence and associated consequences of
TBI. Evaluating history of TBI might be relevant
to a comprehensive assessment of homeless and
marginally housed patients, who often have
complex comorbidities. In addition, public
health research and practice should focus on TBI
prevention and more accurately characterising
the scope and effects of TBI in this vulnerable
population. Although to our knowledge no studies
have been done to evaluate whether incident TBI
is reduced with housing interventions,
randomised trial evidence shows that rent
supplements in combination with intensive case
management substantially improve living
situation, safety, and community
functioning.69
These findings suggest that the
provision of stable housing might also lower the
risk for TBI. High-quality studies are urgently
needed to elucidate the true prevalence and
incidence of TBI, and the directionality of the
relationship between TBI and outcomes in the
homeless and marginally housed population.
69.
Stergiopoulos,
V ∙ Hwang, SW ∙
Gozdzik, A ∙ et
al.
Effect
of
scattered-site
housing
using rent
supplements
and
intensive
case
management
on housing
stability
among
homeless
adults with
mental
illness: a
randomized
trial
JAMA.
2015;
313:905-915
This online publication has been
corrected. The corrected version
first appeared at
thelancet.com/public-health on
December 18, 2019
Contributors
JLS led the title
and abstract screening, full-text screening, risk of
bias assessment, data extraction, statistical
analysis, and drafting of the manuscript. JMS
participated in the title and abstract screening,
full-text screening, risk of bias assessment, and
data extraction. JLS, AET, NDS, AMB, WGH, and WJP
interpreted the results and participated in the
drafting of the manuscript. All authors approved the
final manuscript.
Declaration of
interests
NDS has sat on the
paid advisory board of Highmark Interactive,
received consulting or speaking fees from WorkSafeBC
and Yukon WCB, the National Hockey League, and Major
League Soccer, and has received fees for expert
testimony in neuropsychology. WGH has received
consulting fees or sat on paid advisory boards for
the Canadian Agency for Drugs and Technology in
Health, AlphaSights, Guidepoint, In Silico,
Translational Life Sciences, Otsuka, Lundbeck, and
Newron. WJP is the founder and chief executive
officer of Translational Life Sciences, an early
stage biotechnology company. He is also on the
scientific advisory board of Medipure
Pharmaceuticals and Vitality Biopharma, and in the
past has been on the board of directors for Abattis
Bioceuticals and on the advisory board for Vinergy
Resources; these companies are early stage
biotechnology enterprises with no relation to brain
injury. All other authors declare no competing
interests.
Acknowledgments
This work was
supported by a Canadian Institute of Health
Research Project Grant (#390996). We thank Dean
Giustini at the University of British Columbia
for assistance in developing the search strategy
and Louise Meddings at the University of British
Columbia for her assistance during the drafting
of the manuscript. NDS was supported by the
Michael Smith Foundation for Health Research
Health Professional Investigator Award, and WGH
was supported by the Jack Bell Chair in
Schizophrenia.
Supplementary Material (1)
Supplementary appendix
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